Julia code for the book Numerical Linear Algebra
C++ Matrix -- High performance and accurate (e.g. edge cases) matrix math library with expression template arithmetic operators
A concise library for solving sparse linear systems with direct methods.
Safe and fast mathematical operations with static arrays in the Rust programming language
EMV Compliant QR Library in .NET Standard
Differentiable matrix factorizations using ImplicitDifferentiation.jl.
A linear algebra library that provides a user-friendly interface to several BLAS and LAPACK routines.
Numerical analysis course in Python
🍒 cuRBLAS (Randomized BLAS) is a GPU-accelerated library for accelerating AI and HPC applications.
A parallelized implementation of Principal Component Analysis (PCA) using Singular Value Decomposition (SVD) in OpenMP for C. The procedure used is Modified Gram Schmidt algorithm. The method for Classical Gram Schmidt is also available for use.
QR decomposition, or QR factorization, is a fundamental linear algebra method that decomposes a matrix into a product of an orthogonal matrix and an upper triangular matrix. It is widely used for solving linear least squares problems, computing eigenvalues, Gram-Schmidt, Householder reflections, or Givens rotations.Solver
A linear algebra library for TypeScript and JavaScript
Application for scanning creation and edit QR codes. To scan, point camera on qr code or upload a picture with its image. Result is displayed in field previewed where it can be edited, opened in the browser, or saved in the device’s memory, which allows encrypting not only Internet links, but also any other text like a phone number or email.
A cross compiled Scala.js port of JAMA for JVM, JavaScript, and Scala Native projects.
Fork of the qrupdate library for future maintenance.
Parallelization of QR decomposition with Householder transformation
Matrix decomposition and multiplication on the Cerebras Wafer-Scale Engine (WSE) architecture
Numerical Analysis Problems and Solutions
Matrix Decompostion Techniques - SVD and QR Decomposition
Implementation of the preconditioned Kaczmarz method https://arxiv.org/abs/1903.01806
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